Computer Vision Engineer

Full-Stack Machine Learning Engineer

Role: Full-Time, Long-Term Required: Python Preferred: C++

OVERVIEW

We are seeking a versatile ML engineer to join as a core member of our technical team. This is a long-term position for someone who wants to build sophisticated production systems and grow with a small, focused team. You will work across the entire stack—from data ingestion and feature engineering through model training, validation, and deployment.

The ideal candidate combines strong software engineering fundamentals with deep ML expertise, particularly in time series forecasting and quantitative applications. You should be comfortable operating independently, making architectural decisions, and owning systems end-to-end.

CORE TECHNICAL REQUIREMENTS

Python (Required): Professional-level proficiency writing clean, production-grade code—not just notebooks. Deep understanding of NumPy, Pandas, and their performance characteristics. You know when to use vectorized operations, understand memory management for large datasets, and can profile and optimize bottlenecks. Experience with async programming and multiprocessing is valuable.

Machine Learning (Required): Hands-on experience building and deploying ML systems in production. This goes beyond training models—you understand the full lifecycle: data validation, feature engineering, model selection, hyperparameter optimization, validation strategies, monitoring, and maintenance.

Specific experience we value: gradient boosting frameworks (LightGBM, XGBoost, CatBoost), time series forecasting, probabilistic prediction and uncertainty quantification, feature selection and dimensionality reduction, cross-validation strategies for non-IID data, model calibration.

You should understand overfitting deeply—not just as a concept but as something you actively defend against through proper validation, regularization, and architectural choices.

Data Pipelines (Required): Design and implement robust pipelines handling real-world messiness: missing data, late arrivals, schema changes, upstream failures. You understand idempotency, exactly-once semantics, and backfill strategies. Experience with workflow orchestration (Airflow, Prefect, Dagster) expected. Comfortable with ETL/ELT patterns, incremental vs full recomputation, data quality monitoring, database design and query optimization (PostgreSQL preferred), time series data at scale.

C++ (Preferred): Experience valuable for performance-critical components. Writing efficient C++ and interfacing with Python (pybind11, Cython) is a significant advantage.

HIGHLY DESIRABLE: MULTI-AGENT ORCHESTRATION

We are building systems leveraging LLM-based automation. Experience with multi-agent frameworks highly desirable: LangChain, LangGraph, or similar agent frameworks; designing reliable AI pipelines with error handling and fallbacks; prompt engineering and output parsing; managing context and state across agent interactions. You do not need to be an expert, but genuine interest and hands-on experience will set you apart.

DOMAIN EXPERIENCE: FINANCIAL DATA AND CRYPTO

Preference for candidates with experience in quantitative finance, algorithmic trading, or fintech; cryptocurrency markets and their unique characteristics; financial time series data and forecasting systems; market microstructure, volatility, and regime dynamics. This helps you understand why reproducibility is non-negotiable, why validation must account for temporal structure, and why production reliability cannot be an afterthought.

ENGINEERING STANDARDS

Code Quality: Readable, maintainable code others can modify. Proper version control (meaningful commits, branches, code review). Testing where appropriate. Documentation: docstrings, READMEs, decision records.

Production Mindset: Think about failure modes before they happen. Build in observability: logging, metrics, alerting. Design for reproducibility—same inputs produce same outputs.

Systems Thinking: Consider component interactions, not just isolated behavior. Understand tradeoffs: speed vs accuracy, flexibility vs simplicity. Zoom between architecture and implementation.

WHAT WE ARE LOOKING FOR

Self-Direction: Given a problem and context, you break it down, identify the path forward, and execute. You ask questions when genuinely blocked, not when you could find the answer yourself.

Long-Term Orientation: You think in years, not months. You make decisions considering future maintainability.

Intellectual Honesty: You acknowledge uncertainty and distinguish between what you know versus guess. When something fails, you dig into why.

Communication: You explain complex concepts clearly and document your reasoning.

EDUCATION

University degree in a quantitative/technical field preferred: Computer Science, Mathematics, Statistics, Physics, Engineering. Equivalent demonstrated expertise through work also considered.

TO APPLY

Include: (1) CV/resume, (2) Brief description of a production ML system you built, (3) Links to relevant work if available, (4) Availability and timezone.

Responsibilities:

● Design, develop, and maintain scalable backend services and APIs using Java and Spring

Boot.

● Create and optimize SQL database schemas and queries in PostgreSQL to ensure efficient

data storage and retrieval.

● Implement RESTful APIs to facilitate seamless communication between frontend and backend

components.

● Configure and manage Nginx web servers to efficiently handle incoming requests and improve

application performance.

● Deploy and manage applications on AWS or GCP, ensuring scalability, reliability, and

security.

● Configure and optimize message broker systems using Kafka for real-time data processing

and communication.

● Containerize applications using Docker for easy deployment, scaling, and management.

● Create detailed Low-Level Designs (LLDs) and High-Level Designs (HLDs) to guide the

development and architecture of backend systems.

● Automating CI/CD pipelines and streamlining the software development lifecycle.

● Integrate AI/ML models into backend workflows using Python, PyTorch/TensorFlow, or

third-party AI APIs.

● Leverage AI tools (e.g., OpenAI APIs, Hugging Face, AWS AI services) to build intelligent

features.

● Collaborate closely with frontend developers, product managers, data scientists, and other

stakeholders to deliver high-quality AI-powered solutions.

● Monitor and troubleshoot production systems to ensure optimal performance, reliability, and

uptime.

What We’re Looking For:

● Bachelor’s degree in Computer Science, Engineering, or related field.

● 3-5 years of experience in backend development.

● Proficiency in Java, Spring Boot, PostgreSQL, SQL, and GitActions.

● Strong understanding of RESTful API design principles and best practices.

● Experience with configuring and optimizing Nginx web servers.

● Experience with configuring and optimizing Kafka service.

● Hands-on experience with AWS or GCP.

● Familiarity with Docker containers and container orchestration.

● Ability to create comprehensive Low-Level Designs (LLDs) and High-Level Designs (HLDs)

for backend systems.

● Experience with Python for AI/ML model integration in backend services.

● Familiarity with AI platforms and APIs such as OpenAI, Hugging Face, AWS AI/ML, or GCP

Vertex AI.

● Excellent problem-solving skills and attention to detail.

● Strong communication and collaboration skills, with the ability to work effectively in a team

environment.

Preferred Qualifications:

● Knowledge of microservices architecture and related technologies.

● Experience with cloud-native development and serverless computing.

● Understanding of software development best practices, including Agile methodologies

🚀 Were Hiring: Staff Engineer – Computer Vision & Machine Learning 🚀

📍 Location: Gurugram

💼 Experience: 7-10 Years

About the Role

We are seeking a passionate Computer Vision and Machine Learning expert to develop advanced solutions in medical imaging. If you’re excited about challenges like image segmentation, object detection, and 3D reconstruction, let’s connect!

Mandatory Technical Skills:

✅ Programming Languages: Proficiency in C++, Python, and C#.

✅ Computer Vision Expertise: Experience with OpenCV for tasks such as:

• Image Segmentation
• Object Detection
• Pattern Recognition
• 3D Reconstruction
• ✅ ML/DL Frameworks: Proficiency in TensorFlow, PyTorch; hands-on experience with models like YOLO, U-Net, ResNet, VGG.
• ✅ Image Processing: Strong understanding of:
• Color-space transformations
• Histogram/Contrast enhancement
• Morphology and frequency domain filtering
• ✅ Medical Imaging Knowledge: Familiarity with modalities like CT, MRI, Ultrasound.
• ✅ Algorithms & Data Structures: Solid problem-solving, optimization, and analytical skills.

Additional Preferred Skills:

🔹 Advanced C++ (STL, multithreading, design patterns).

🔹 Python libraries: Numpy, Pandas, Scikit-learn.

🔹 Knowledge of tools like VTK, ITK, or MITK.

🔹 Understanding of healthcare regulations (e.g., FDA, CE).

Why This Role?

You’ll build cutting-edge Computer Vision and Machine Learning solutions for healthcare, making a meaningful impact on lives.

Sizzle is an exciting new startup that’s changing the world of gaming.  At Sizzle, we’re building AI to automate gaming highlights, directly from Twitch and YouTube streams. We’re looking for a superstar Python expert to help develop and deploy our AI pipeline. The main task will be deploying models and algorithms developed by our AI team, and keeping the daily production pipeline running. Our pipeline is centered around several microservices, all written in Python, that coordinate their actions through a database. We’re looking for developers with deep experience in Python including profiling and improving the performance of production code, multiprocessing / multithreading, and managing a pipeline that is constantly running. AI/ML experience is a plus, but not necessary. AWS / docker / CI/CD practices are also a plus. If you are a gamer or streamer, or enjoy watching video games and streams, that is also definitely a plus :-)

You will be responsible for:

• Building Python scripts to deploy our AI components into pipeline and production
• Developing logic to ensure multiple different AI components work together seamlessly through a microservices architecture
• Managing our daily pipeline on both on-premise servers and AWS
• Working closely with the AI engineering, backend and frontend teams

You should have the following qualities:

• Deep expertise in Python including:
• Multiprocessing / multithreaded applications
• Class-based inheritance and modules
• DB integration including pymongo and sqlalchemy (we have MongoDB and PostgreSQL databases on our backend)
• Understanding Python performance bottlenecks, and how to profile and improve the performance of production code including:
• Optimal multithreading / multiprocessing strategies
• Memory bottlenecks and other bottlenecks encountered with large datasets and use of numpy / opencv / image processing
• Experience in creating soft real-time processing tasks is a plus
• Expertise in Docker-based virtualization including:
• Creating & maintaining custom Docker images
• Deployment of Docker images on cloud and on-premise services
• Experience with maintaining cloud applications in AWS environments
• Experience in deploying machine learning algorithms into production (e.g. PyTorch, tensorflow, opencv, etc) is a plus
• Experience with image processing in python is a plus (e.g. openCV, Pillow, etc)
• Experience with running Nvidia GPU / CUDA-based tasks is a plus (Nvidia Triton, MLFlow)
• Knowledge of video file formats (mp4, mov, avi, etc.), encoding, compression, and using ffmpeg to perform common video processing tasks is a plus.
• Excited about working in a fast-changing startup environment
• Willingness to learn rapidly on the job, try different things, and deliver results
• Ideally a gamer or someone interested in watching gaming content online

Seniority: We are looking for a mid to senior level engineer

Salary: Will be commensurate with experience. 

Who Should Apply:

If you have the right experience, regardless of your seniority, please apply.

Work Experience:  4 years to 8 years

About Sizzle

Sizzle is building AI to automate gaming highlights, directly from Twitch and YouTube videos. Sizzle works with thousands of gaming streamers to automatically create highlights and social content for them. Sizzle is available at www.sizzle.gg.